The impact of weather conditions on bikeshare trips in Washington,DC

Bicycle usage can be affected by colder weather, precipitation, and excessive heat. The research presented here analyzes the effect of weather on the use of the Washington, DC, bikeshare system, exploiting a dataset of all trips made on the system. Hourly weather data, including temperature, rainfall, snow, wind, fog, and humidity levels are linked to hourly usage data. Statistical models linking both number of users and duration of use are estimated. Further, we evaluate trips from bikeshare stations within one quarter mile of Metro (subway) stations at times when Metro is operating. This allows us to determine whether Metro serves as a back-up option when weather conditions are unfavorable for bicycling. Results show that cold temperatures, rain, and high humidity levels reduce both the likelihood of using bikeshare and the duration of trips. Trips taken from bikeshare stations proximate to Metro stations are affected more by rain than trips not proximate to Metro stations and less likely when it is dark. This information is useful for understanding bicycling behavior and also for those planning bikeshare systems in other cities.     

Promoting bike-and-ride: The Dutch experience

The number of policy initiatives to promote the use of bike-and-ride, or the combined use of bicycle and public transport for one trip, has grown considerably over the past decade as part of the search for more sustainable transport solutions. This paper discusses the experiences with, and impacts of, such initiatives in the Netherlands. The Dutch measures to promote bicycle use in access trips have been generally successful. A country-wide program to upgrade regular and secure bicycle parking at train stations has led to an increase in user satisfaction and a growth in bicycles parked at stations. Smaller programs to stimulate the combined use of bike-and-bus have resulted in an increase in bicycle use, bus use, and share of infrequent bus passengers. Bicycle lockers at bus stops are hardly used by bus passengers, due in part to the dominance of students among bus users as well as the relatively high price of lockers in comparison to the value of bicycles used for access trips. Measures to promote the use of the bicycle in egress trips have met with more varying results. Projects to introduce leasing bicycles for egress trips have failed to attract passengers, for both train and bus services. In contrast, the introduction of flexible rental bicycles at train stations has resulted in a small reduction in car use, growth in train trips, and growth in bicycle use for non-recurrent trips. The Dutch experiences suggest some lessons for promoting bike-and-ride in countries and cities with a less well-developed bicycle infrastructure.     

How does our natural and built environment affect the use of bicycle sharing?

Public bicycle-sharing programs (PBSP) are short-term bicycle hire systems. In recent years their popularity has soared. This study examined Brisbane’s CityCycle scheme, the largest PBSP in Australia, and investigated the role of (natural and built) environmental features on usage. The study addressed four research questions: (1) What are the dynamics of PBSP use in terms of travel time, speed, and distance? (2) What is the relationship between PBSP participation and cycling infrastructure? (3) How does land-use affect PBSP usage? (4) How does topography affect PBSP usage? To answer these four questions, the authors analysed large existing datasets on CityCycle usage, land-use, topography, and cycling infrastructure, which were each obtained through multiple sources. Correlation and regression analysis were employed to establish significant relationships amongst variables. It was found that: most users take short trips within the free initial period provided under the CityCycle scheme and do not incur any charges other than for membership; PBSP use is strongly correlated with the length of off-road bikeways near each CityCycle station; CityCycle is more frequently used on weekends for recreational purposes; loop journeys, which are also associated with leisure trips, are popular in Brisbane, especially on weekends; leisure trips are taken at a relatively slower pace than utilitarian trips; during weekdays, a trimodal peak is clearly evident, with PBSP commute trips in the morning and evening peaks and a smaller but significant peak around lunchtime; and users avoid returning CityCycle bicycles to stations located on hilltops. These findings can collectively enhance both the siting and design of PBSP, thereby optimizing investments in sustainable mobility.     

Modelling the potential for cycling in access trips to bus,train and metro in Rio de Janeiro

Most studies that address the integration of cycling and public transport (PT) focus on developed countries and deal with multi-modal bicycle-train trips. Little is known about the integration of cycling and other main modes such as bus and metro, especially in developing countries, where entirely different socio-economic and trip making conditions prevail. The aim of this study is to model the propensity of current PT users to shift to the bicycle in access trips to bus stops, train and metro stations in Rio de Janeiro, Brazil. Interviews were conducted to collect data on the socio-economic characteristics of the interviewee, trip and spatial characteristics and self-reported barriers and motivators for bicycle use. Two binary logit models were estimated to predict the main factors affecting the propensity to use a bicycle as feeder mode to PT. The results show that socio-economic characteristics as well as barriers and motivators are important factors to explain propensity for bike and ride. The barriers’ model reveals that personal constraints, living too close to the PT boarding point, current parking conditions and public safety play a role. For the motivators’ model, changing home location, owning a bicycle, implementation of cycle ways and improvement in parking conditions are explanatory. Policy recommendations are formulated to increase bicycle ownership and improve cycling infrastructure.     

Stochastic frontier analysis of excess access to mid-trip battery electric vehicle fast charging

This study aims to explore how factors including charging infrastructure and battery technology associate the way people currently charge their battery electric vehicles, as well as to explore whether good use of battery capacity can be encouraged. Using a stochastic frontier model applied to panel data obtained in a field trial on battery electric vehicle usage in Japan, the remaining charge when mid-trip fast charging begins is treated as a dependent variable. The estimation results obtained using four models, for commercial and private vehicles, respectively, on working and non-working days, show that remaining charge is associated with number of charging stations, familiarity with charging stations, usage of air-conditioning or heater, battery capacity, number of trips, Vehicle Miles of Travel, paid charging. However, the associated factors are not identical for the four models. In general, EVs with high-capacity batteries are initiated at higher remaining charge, and so are the mid-trip fast charging events in the latter period of this trial. The estimation results also show that there are great opportunities to encourage more efficient charging behavior. It appears that the stochastic frontier modeling method is an effective way to model the remaining charge at which fast-charging should be initiated, since it incorporates trip and vehicle characteristics into the estimation process to some extent.     

Roadmap for free-floating bikeshare research and practice in North America

ABSTRACT

The deployment of smartphone-operated, non-station-based bicycle fleets (“dockless” or “free-floating” bikeshare) represents a new generation of bikesharing. Users locate bikes in these free-floating systems using Global Positioning Systems (GPS) and lock bikes in place at their destinations. In this paper, we review current free-floating bikesharing systems in North America and discuss priorities for future research and practice. Since launching in 2017, free-floating bikeshare has expanded rapidly to encompass 200+ systems operating 40,000+ bikes within 150+ cities. In contrast with previous systems, free-floating systems operate almost exclusively using commercial “for-profit” models, amidst concerns of financial sustainability. Governance for these systems is in early stages and can include operating fees, fleet size caps, safety requirements, parking restrictions, data sharing, and equity obligations. We identify research and practice gaps within the themes of usage, equity, sharing resources, business model, and context. While some existing bikesharing literature translates to free-floating systems, novel topics arise due to the ubiquity, fluidity, and business models of these new systems. Systems have numerous obstacles to overcome for long-term sustainability, including barriers common to station-based systems: limited supportive infrastructure, equity, theft or vandalism, and funding. Other unique obstacles arise in free-floating bikeshare around parking, sidewalk right of ways, varied bicycle types, and data sharing. This review offers background in and critical reflection on the rapidly evolving free-floating bikeshare landscape, including priorities for future research and practice. If concerns can be overcome, free-floating bikeshare may provide unprecedented opportunities to bypass congested streets, encourage physical activity, and support urban sustainability.     

Exploring the link between the neighborhood typologies,bicycle infrastructure and commuting cycling over time and the potential impact on commuter GHG emissions

This paper investigates the evolution of urban cycling in Montreal, Canada and its link to both built environment indicators and bicycle infrastructure accessibility. The effect of new cycling infrastructure on transport-related greenhouse gas (GHG) emissions is then explored. More specifically, we aim at investigating how commuting cycling modal share has evolved across neighborhood built-environment typologies and over time in Montreal, Canada. For this purpose, automobile and bicycle trip information from origin–destination surveys for the years 1998, 2003 and 2008 are used. Neighborhood typologies are generated from different built environment indicators (population and employment density, land use diversity, etc.). Furthermore, to represent the commuter mode choice (bicycle vs automobile), a standard binary logit and simultaneous equation modeling approach are adopted to represent the mode choice and the household location. Among other things, we observe an important increase in the likelihood to cycle across built environment types and over time in the study region. In particular, urban and urban-suburb neighborhoods have experienced an important growth over the 10 years, going from a modal split of 2.8–5.3% and 1.4–3.0%, respectively. After controlling for other factors, the model regression analysis also confirms the important increase across years as well as the significant differences of bicycle ridership across neighborhoods. A statistically significant association is also found between the index of bicycle infrastructure accessibility and bike mode choice – an increase of 10% in the accessibility index results in a 3.7% increase in the ridership. Based on the estimated models and in combination with a GHG inventory at the trip level, the potential impact of planned cycling infrastructure is explored using a basic scenario. A reduction of close to 2% in GHG emissions is observed for an increase of 7% in the length of the bicycle network. Results show the important benefits of bicycle infrastructure to reduce commuting automobile usage and GHG emissions.     

Exploring the impact of walk–bike infrastructure,safety perception,and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.     

Fast-charging station choice behavior among battery electric vehicle users

This study explores how battery electric vehicle users choose where to fast-charge their vehicles from a set of charging stations, as well as the distance by which they are generally willing to detour for fast-charging. The focus is on fast-charging events during trips that include just one fast-charge between origin and destination in Kanagawa Prefecture, Japan. Mixed logit models with and without a threshold effect for detour distance are applied to panel data extracted from a two-year field trial on battery electric vehicle usage in Japan. Findings from the mixed logit model with threshold show that private users are generally willing to detour up to about 1750 m on working days and 750 m on non-working days, while the distance is 500 m for commercial users on both working and non-working days. Users in general prefer to charge at stations requiring a shorter detour and use chargers located at gas stations, and are significantly affected by the remaining charge. Commercial users prefer to charge at stations encountered earlier along their paths, while only private users traveling on working days show such preference and they turn to prefer the stations encountered later when choosing a station in peak hours. Only private users traveling on working days show a strong preference for free charging. Commercial users tend to pay for charging at a station within 500 m detour distance. The fast charging station choice behavior is heterogeneous among users. These findings provide a basis for early planning of a public fast charging infrastructure.     

Who cycles more? Determining cycling frequency through a segmentation approach in Montreal,Canada

The decision to cycle frequently in an urban setting is a complex process and is affected by a variety of factors. This study analyzed the various factors influencing cycling frequency among 1707 cyclists from Montreal, Canada using an ordinal logistic regression. A segmentation of cyclists is used in a series of ordinal logistic models to better understand the different impacts of variables on the frequency of cycling among each group of cyclists for commute and for utilitarian purposes. Our models show a variation in the impacts of each dependent variable on frequency of cycling across the various segments of cyclists. Mainly making cyclists feel safe not only on bicycle specific infrastructure but also on regular streets, emphasizing the low cost, convenience and improving the opinion on cycling in the population are effective interventions to increase bicycle usage. Also, it was shown that women were less likely to cycle to work than men, but more likely to cycle for other utilitarian trips, pointing at the presence of specific barriers to commuting for woman. Although the findings from this study are specific to Montreal, they can be of interest to transportation planners and engineers working toward increasing cycling frequency in other regions.     

Evaluating unintended outcomes of regional smart-growth strategies: Environmental justice and public health concerns

Many urban areas are perusing infill, transit oriented, and other “smart-growth” strategies to address a range of important regional goals. Denser and more mixed use urban development may increase sustainability and improve public health by reducing vehicle travel and increasing the share of trips made by transit, walking and bicycling. Fewer vehicle trips results in fewer greenhouse gas and toxic vehicle emissions, and more trips made by walking and bicycle increases physical activity. Prior research has largely focused on modeling and estimating the potential size of these and other smart-growth strategy benefits. A largely overlooked area is the potential for unexpected public health costs and environmental justice concerns that may result from increasing density. We evaluate regional land-use and transportation planning scenarios developed for the year 2040 by a metropolitan planning organization with a newly developed regional air quality modeling framework. Our results find that a set of regional plans designed by the MPO to promote smart-growth that are estimated to result in less vehicle use and fewer vehicle emissions than a more typical set of plans results in higher population exposure to toxic vehicle emissions. The smart-growth plans also result in greater income-exposure inequality, raising environmental justice concerns. We conclude that a more spatially detailed regional scale air quality analysis can inform the creation of smarter smart-growth plans.     

Charging infrastructure planning for promoting battery electric vehicles: An activity-based approach using multiday travel data

This paper studies electric vehicle charger location problems and analyzes the impact of public charging infrastructure deployment on increasing electric miles traveled, thus promoting battery electric vehicle (BEV) market penetration. An activity-based assessment method is proposed to evaluate BEV feasibility for the heterogeneous traveling population in the real world driving context. Genetic algorithm is applied to find (sub)optimal locations for siting public charging stations. A case study using the GPS-based travel survey data collected in the greater Seattle metropolitan area shows that electric miles and trips could be significantly increased by installing public chargers at popular destinations, with a reasonable infrastructure investment.     

Dockless bike-sharing systems: what are the implications?

ABSTRACT

The emergence of dockless bike-sharing services has revolutionised bike-sharing markets in recent years, and the dramatic growth of shared bike fleets in China, as well as their rapid expansion throughout the world, exceeds prior expectations. An understanding of the impacts of these new dockless bike-sharing systems is of vital importance for system operations, transportation and urban planning research. This paper provides a first overview of the emerging literature on implications of dockless bike-sharing systems for users' travel behaviour, user experience, and relevant social impacts of dockless bike-sharing systems. Our review suggests that the dockless design of bike-sharing systems significantly improves users' experiences at the end of their bike trips. Individuals can instantly switch to a dockless shared bike without the responsibility of returning it back to a designated dock. Additionally, the high flexibility and efficiency of dockless bike-sharing often makes the bike-sharing systems' integration with public transit even tighter than that of traditional public bikes, providing an efficient option for first/last-mile trips. The GPS tracking device embedded in each dockless shared bike enables the unprecedented collection of large-scale riding trajectory data, which allow scholars to analyse people's travel behaviour in new ways. Although many studies have investigated travel satisfaction amongst cyclists, there is a lack of knowledge of the satisfaction with bikeshare trips, including both station-based and dockless bikeshare systems. The availability and usage rates of dockless bike-sharing systems implies that they may seriously impact on individuals' subjective well-being by influencing their satisfaction with their travel experiences, health and social participation, which requires further exploration. The impact of dockless bike-sharing on users' access to services and social activities and the related decreases in social exclusion are also relevant issues about which knowledge is lacking. With the increases in popularity of dockless shared bikes in some cities, issues related to the equity and access and the implications for social exclusion and inequality are also raised.     

The accessibility of railway stations: the role of the bicycle in The Netherlands

The market potential of railway services depends on the quality of the total chain from residence to place of activity. In The Netherlands where natural conditions and infrastructure are conducive, the bicycle is a potentially attractive access mode for railways since it allows travellers to avoid waiting at bus, metro or tram stops. Especially at the home end the bicycle appears to play a large role as an access mode with a share of 35%. At the activity end the share is much shorter. Implications are discussed for policies aiming at increasing the share of multimodal trips. Also physical planning implications are considered.     

The use of the bicycle

The rediscovery of the bicycle by the public, by politicians and by professional urban transportation planners as a mode of transport which is perfectly in harmony with the goals of environmental protection, energy saving and personal fitness has stimulated this empirical study on the actual use of the bicycle by various population groups for obligatory and discretionary trip purposes. The influence on bicycle usage of such factors as age, education, car availability, residential density and town size, topography and time of year is analysed in this paper for selected population groups. For housewives from motorized households logit‐models were designed and calibrated to model their modal choice for shopping trips with special references to the bicycle. From the empirical results, the groups with the largest potentials for cycling are identified and the extent to which the potentials could be activated by specific policies is discussed. The research is based on a large sample held to be representative for the Federal Republic of Germany in 1976 and is supplemented by more recent surveys in selected German cities conducted by SOCIALDATA Munich.     

The bicycle as a feedering mode: experiences from three European countries

Bike-and-ride, or the combined use of bicycle and public transport for one trip, is a multimodal alternative for the car. This paper discusses the use of bike-and-ride in three countries with widely differing bicycle cultures and infrastructures: the Netherlands, Germany and the UK. The share of the bicycle in access trips is comparable to general levels of bicycle ridership in each country, but only for train services and other fast modes of public transport. Strong similarities are found in the characteristics of bike-and-ride trips and users, in terms of travel distances, travel motives, and the impact of car availability. The majority of bike-and-ride users travels between 2 and 5 km to a public transport stop, with longer access distances reported for faster modes of public transport. Work and education are the main travel motives, with the first dominating the faster modes and the second the slower modes of public transport. Car availability hardly influences the choice for a combined use of bicycle and train, but strongly affects the levels of bike-and-ride for slower modes of transport.     

Characterising group-cycling journeys using interactive graphics

The group-cycling behaviours of over 16,000 members of the London Cycle Hire Scheme (LCHS), a large public bikeshare system, are identified and analysed. Group journeys are defined as trips made by two or more cyclists together in space and time. Detailed insights into group-cycling behaviour are generated using specifically designed visualization software. We find that in many respects group-cycle journeys fit an expected pattern of discretionary activity: group journeys are more likely at weekends, late evenings and lunchtimes; they generally take place within more pleasant parts of the city; and between individuals apparently known to each other. A separate set of group activity is found, however, that coincides with commuting peaks and that appears to be imposed onto LCHS users by the scheme’s design. Studying the characteristics of individuals making group journeys, we identify a group of less experienced LCHS cyclists that appear to make more spatially extensive journeys than they would do normally while cycling with others; and that female cyclists are more likely to make late evening journeys when cycling in groups. For 20% of group cyclists, the first journey ever made through the LCHS was a group journey; this is particularly surprising since just 9% of all group cyclists’ journeys are group journeys. Moreover, we find that women are very significantly (p < 0.001) overrepresented amongst these ‘first time group cyclists’. Studying the bikeshare cyclists, or bike share ‘friends’, that individuals make ‘first time group journeys’ with, we find a significantly high incidence (p < 0.001) of group journeys being made with friends of the opposite gender, and for a very large proportion (55%) of members these first ever journeys are made with a friend that shares the same postcode. A substantial insight, then, is that group cycling appears to be a means through which early LCHS usage is initiated.     

Long-term impacts of transport infrastructure networks on land-use change: an international review of empirical studies

Improvements in geographical information systems, the wider availability of high-resolution digital data and more sophisticated econometric techniques have all contributed to increasing academic interest and activity in long-term impacts of transport infrastructure networks (TINs) on land use (LU). This paper provides a systematic review of recent empirical evidence from the USA, Europe and East Asia, classified regarding the type of transport infrastructure (road or rail), LU indicator (land cover, population or employment density, development type) and outcome (significance, relationship’s direction) as well as influential exogenous factors. Proximity to the rail network is generally associated with population growth (particularly soon after the development of railway infrastructure), conversion to residential uses and the development of higher residential densities. Meanwhile, proximity to the road network is frequently associated with increases in employment densities as well as the conversion of land to a variety of urban uses including commercial and industrial development. Compared with road infrastructure, the impact of rail infrastructure is often less significant for land cover or population and employment density change. The extent of TINs’ impact on LU over time can be explained by the saturation in TIN-related accessibility and LU development.     

Determining the role of bicycle sharing system infrastructure installation decision on usage: Case study of montreal BIXI system

The traditional quantitative approach to studying Bicycle Sharing System (BSS) usage involves examining the influence of BSS infrastructure (such as number of BSS stations and capacity), transportation network infrastructure, land use and urban form, meteorological data, and temporal characteristics. These studies, as expected, conclude that BSS infrastructure (number of stations and capacity) have substantial influence on BSS usage. The earlier studies consider usage as a dependent variable and employ BSS infrastructure as an independent variable. Thus, in the models developed, the unobserved factors influencing the measured dependent variable (BSS usage) also strongly influence one of the independent variables (BSS infrastructure). This is a classic violation of the most basic assumption in econometric modeling i.e. the error component in the model is not correlated with any of the exogenous variables. The model estimates obtained with this erroneous assumption are likely to over-estimate the impact of BSS infrastructure. Our research effort proposes an econometric framework that remedies this drawback. We propose a measurement equation to account for the installation process and relate it to the usage equations thus correcting for the bias introduced in earlier research efforts by formulating a multi-level joint econometric framework. The econometric models developed have been estimated using data compiled from April 2012 to August 2012 for the BIXI system in Montreal. The model estimates support our hypothesis and clearly show over-estimation of BSS infrastructure impacts in models that neglect the installation process. An elasticity analysis to highlight the advantages of the proposed econometric model is also conducted.     

The effect of non-recreational transport cycling on use of other transport modes: A cross-sectional on-line survey

Accurate modelling of the health and environmental benefits of non-recreational transport cycling requires information about its effects on the use of other transport modes. Relevant research has not focussed on cycling for transport in a general context (as opposed to bikeshare), nor allowed for multi-modal trips. The influence of trip- and personal-characteristics on whether cycling replaces car-driving have yet to be considered. The present study aimed to address these research gaps. An on-line cross-sectional survey was completed by 1525 Australians who cycle for transport at least once per week. For the most recent trip completed (at least partly) by bicycle participants provided trip distance, and percentage travelled by car, public transport (PT), and walking. They also provided the percentage travelled by each mode for the same trip before taking up transport cycling; and a hypothetical future trip when riding is not possible. Compared to the same trip before, fifty percent of recent trips reduced car use, and around 1/3 eliminated a 100%-car trip. Reduced car use was significantly less likely for trips under 7.5 km, commuting, females, respondents under 55, and regular cyclists. Reduced car use was less likely for respondents who started riding because it is flexible, and more likely for those who started riding to avoid parking. Car-use was reduced by an average of 6.2 km per trip, and each bicycle-km cycled replaced 0.5 car-km. Participants report that since taking up cycling, even when they cannot use their bike, they use cars less and use PT more compared to before they took up cycling. Results suggest that previous studies underestimated the extent to which transport cycling replaces car travel, and highlights trip types and population groups to target with cycling promotion strategies. Information about the per-trip and per-bicycle-km replacement of car, PT and walking may be used for more accurate estimation of the benefits of transport cycling than has hitherto been possible.